In this post, you will learn how to create an AWS Application Load Balancer (ALB) for your EC2 instances running a Spring Boot application. You will also create an Autoscaling Group (ASG) which will simplify the setup and will automatically scale-in and scale-out.Continue reading “How to Create an AWS ALB and ASG”
In this post, you will learn how easy it is to create a virtual machine with AWS EC2. You will learn the basics and as an example, you will deploy and run a basic Spring Boot application. Enjoy!Continue reading “How to Create an AWS EC2 VM”
In our previous post, we showed how to create an AWS Continuous Deployment Pipeline. This post will continue where we left off. We will enhance the pipeline with a Review stage, a more efficient use of the Maven cache and add notifications to the pipeline.Continue reading “How to Create an AWS Continuous Deployment Pipeline Cont’d”
Creating a continuous deployment pipeline will bring us a step closer to an automated build, test, deploy strategy. In order to create such a pipeline, we need to have access to several tools. Instead of installing these on on-premise servers, we can make use of the AWS cloud offer. Let’s see how this can be accomplished!Continue reading “How to Create an AWS Continuous Deployment Pipeline”
In this post, we will create a Spring Cloud Function and create some unit tests for it. We will do so by creating a function with Bean definition and with the functional style. At the end, we will deploy the function on AWS Lambda.Continue reading “How to Deploy a Spring Cloud Function on AWS Lambda”
In this post, we are going to explore how we can deploy a simple Spring Boot application to AWS Elastic Beanstalk. We will explain how to setup an AWS account and provide a step-by-step guide how to deploy to AWS.Continue reading “How to Deploy a Spring Boot App to AWS Elastic Beanstalk”
In this post, we will take a look at how we can make services be aware of each other without knowing their exact location. We will make use of Eureka Server which will act as a Discovery Server. Being Spring fans, we will do so by means of Spring Eureka.
In this post, we will take a look at how we can use Google Cloud Vision from a Spring Boot application. With Google Cloud Vision it is possible to derive all kinds of things from images, like labels, face and text recognition, etc. As a bonus, some examples with Python are provided too.
You are looking for an easy way to automatically build your application in the Cloud? Then maybe Google Cloud Platform (GCP) Cloud Build is something for you. In this post, we will build a Spring Boot Maven project with Cloud Build, create a Docker image for it and push it to GCP Container Registry.
In this post we are going to deploy a Spring Boot application to the Google Cloud Platform (GCP) App Engine. First, we will take a look at the differences between the standard and flexible environment of App Engine. After that, we will describe step by step how the deployment to GCP App Engine can be accomplished.